What to do with all that customer data
When analyzing customer data, it’s easy to miss the forest for the trees when bombarded with social media engagements, ad clicks, and email opens, not to mention each customer’s complete purchase history. Decision makers today have access to so much data, it’s often paralyzing to decide which metrics to focus on and what numbers to ignore. Maximizing revenue requires the right way to quantify customers, and the right way to use that information.
That’s where customer lifetime value (CLV) comes in. CLV is a single metric that estimates how much value any given customer will bring to your business over the course of the total time they interact with your brand—past, present, and future.
Rather than focusing too heavily on social activity, or simply on the total value of their first few purchases, you can quantify customers by their projected future lifetime revenue.
It’s important to calculate CLV at the individual customer level to get the most out of this metric. Average CLVs across customer channels or segments can tell you a lot about your customer base, but individual CLVs allow you to quantify any grouping of customers. You can segment by any customer behavior or attribute, or even rank individual customers.
Once you have an estimated CLV for each of your customers, it’s time to pivot your marketing, product, sales, engagement/retention, and even customer service strategy to align with the goal of increasing customer lifetime value.
Once you’ve calculated CLV, you can use it to determine your target customer acquisition cost (CAC). Instead of simply targeting customers that bring in high initial revenue, focus your targeting and acquisition efforts on high CLV customers. Even if some of their first purchases might be small, they will bring your business more value in the long run.
More specifically, a customer acquisition is unprofitable only if their acquisition cost exceeds their lifetime margin—not just the margin of their first purchase. For most businesses, it makes sense to keep a CLV to CAC ratio around 3:1 for each marketing segment. Spend too much (like a 1:1 ratio) and acquiring these customers won’t be profitable. However, spend too little (like a 7:1 ratio), and you’ll be missing out on profitable customers whose acquisition cost is above your current bid cap.
Essentially, this strategy will allocate less marketing budget to low CLV customers and more to high CLV customers. It will ensure that all customer acquisitions are profitable, since low CLV customers will be acquired only when a low CAC is enough. Plus, it will ensure that you acquire the maximum number of profitable, high CLV customers by remaining open to high acquisition costs for customers who will be very valuable in the long run.
For even more improvements, Retina utilizes mathematical optimization to find the absolute best CACs, while hitting revenue and acquisition targets simultaneously. In short, setting CAC based on CLV will enable any business to acquire the maximum number of profitable customers in every one of their segments.
Once new customers have been acquired, the return on investment (ROI) of any marketing campaign should be measured via CLV. Typically, demand side platforms measure return on advertising spend by comparing CAC to the revenue of a customer’s first purchase. But that metric of marketing ROI is deeply flawed.
Some newly acquired customers will be worth a ton over the course of their lifetime, while others are worth no more than their first purchase. Even a customer who starts a small, very long subscription is worth more than a medium sized one-time purchase. Projected lifetime value is the key factor to decide whether the acquisition cost was money well spent. Measuring ROI of marketing campaigns in any other way misrepresents the ultimate value of each new customer to your brand and will lead to suboptimal marketing decisions.
To determine the lifetime value of newly acquired customers, traditional methods require businesses to wait for a customer to have three to four transactions before calculating CLV. Retina uses early customer lifetime value predictive analytics to determine CLV after just one transaction or, in some cases, even before the first transaction. Because your primary goal is to acquire customers with the highest possible CLV, an early calculation is critical to optimize campaigns. You can’t rely on the first purchase data alone or wait for four transactions to measure ROI. Early CLV is crucial to dynamically measure the ROI of new campaigns and optimize them accordingly.
CLV data can also illuminate which products inspire repeat purchases and which products spell the beginning and end of a customer’s journey. Focus on those products correlated with high CLV: feature the products prominently on websites, social media, and advertising to extend customer lifespan and boost sales overall. Find out why your high CLV customers favor those products. Do they have a feature that people love? Is that product your brand’s flagship experience? A customer’s first product experience with your brand will make or break their trust in you. Always strive to have new customers start with a great product.
For products associated with low CLV, it may be that a poor product experience is driving customers away. Consider retiring those products to avoid bad customer experiences that don’t represent your brand’s high quality standards. Keep in mind that those products may not be profitable after accounting for their impact on lifetime value, especially if you’re also spending budget to advertise them. Retiring products will save costs on inventory and allow your team to focus on higher CLV products or future development.
For products that don’t significantly impact CLV either way, dig into customer reviews and survey responses to see how the products can be improved. Whether it’s product design, customer support, price, or another factor, spend time and budget making improvements to boost the associated CLV for these products.
Most sales teams take the same actions for every customer. Better teams attempt to optimize their time for maximum revenue. They achieve heightened efficiency by focusing on the most eager leads, or better yet, focusing on the leads who are interested in a high revenue first purchase.
However, the optimal strategy is for sales teams to focus on customers with the highest lifetime value. CLV-specific marketing campaigns intrinsically categorize the resulting prospects as low, medium, or high estimated CLV. Typically, the lack of customer purchasing history makes it impossible to model CLV for new customers. Retina’s early customer lifetime value technology means we can provide customer-specific CLV predictions before a customer’s first transaction.
The greatest mistake in sales prioritization is to let high CLV customers fall by the wayside while your sales team focuses on closing low CLV leads. Empowered by CLV insights, sales teams can finally avoid this painful inefficiency. Sales reps can prioritize follow-up activities by customer CLV to ensure they reach out to the most profitable new customers first. Further, time spent communicating with leads can be informed by CLV, so that reps spend generous time communicating with high CLV leads, while keeping low CLV communications short.
In the same way that companies are adjusting their sales and marketing strategies to focus on high CLV customers, the priorities around customer service can shift to focus on those customers as well. But in customer service, it’s important to focus on customers that are likely to churn soon as well as customers that are the most valuable to your business.
Retina’s customer-level CLV is generated in tandem with predictions of customer churn. Knowing that a customer may churn soon should be a big factor when prioritizing service tickets.
Customers with high CLV are likely to stick around for a long time and potentially spend much more with your brand. If one of them has a problem, it needs to get fixed immediately and diligently.
It follows that businesses should use the unique CLV and anticipated churn date associated with every customer individually to prioritize their customer service tickets.
Customer outreach efforts seek to re-engage customers, keeping them purchasing your products again and again. However, not all customers are the same. Customers differ in the likelihood that they will purchase again and in the expected revenue they will generate for your brand in the future.
In the course of their customer journey, many customers will feel unsure if they will purchase from your business again. In that key moment of indecision, successful customer outreach can pivot a customer’s journey from the possibility of churning to long-term retention. However, placing that exact moment is impossible for most businesses. Reaching out to stable customers may be a waste of resources or may even annoy them. Meanwhile, reaching out to an upset customer might be too little, too late.
Retina’s customer churn predictions identify customers who are just starting to be at risk of churning. Reaching out to exactly those customers at the right time boosts retention far more effectively than sending an impersonal mass email.
Retina’s team of data scientists can not only calculate customer lifetime value for each of your customers, we can also provide actionable insights for how to grow your business. To learn more, explore our free Shopify tool Retina Go! or get in touch with us for a customized solution at [email protected].